Content
- The CPI base revision exercise measures a slice of life
- The Constitution enters the sanctum
The CPI base revision exercise measures a slice of life
Source :The Hindu
Why in News?
CPI Base Revision (2012 → 2024)
- MoSPI revising CPI base year to 2024 using HCES 2023–24, reflecting new consumption patterns, digital spending, and services share, improving inflation measurement for better monetary policy and welfare indexation.
- Revision captures structural changes like urbanisation, income growth, platform-based consumption, ensuring CPI mirrors current household budgets and prevents policy errors arising from outdated consumption weights and baskets.
Relevance
GS III (Economy)
- Inflation measurement, monetary policy transmission, real incomes, macroeconomic stability
- Links to RBI inflation targeting, fiscal policy calibration, poverty estimation, wage indexation
- Static areas: CPI vs WPI vs GDP Deflator, demand-pull vs cost-push inflation
Practice Question
- “Accurate inflation measurement is as important as inflation control.” Discuss in the context of CPI base revision in India.(250 Words)
Basics
Inflation — Meaning
- Inflation is a sustained increase in general price levels, reducing purchasing power and real incomes, especially harming fixed-income earners and poor households, making inflation control a core macroeconomic objective.
- It differs from temporary price shocks; persistent inflation influences savings, investments, interest rates, and exchange rates, shaping overall macroeconomic stability and growth prospects.
Consumer Price Index (CPI)
- CPI measures retail inflation by tracking price changes in a representative basket of goods and services consumed by households across rural and urban India, reflecting cost-of-living pressures.
- It converts everyday expenses like food, housing, fuel, and services into a statistical index, linking household experience with official inflation measurement for policy decisions.
CPI vs WPI
- CPI captures retail and services inflation faced by consumers, whereas WPI measures wholesale price movements, largely goods-centric, making CPI more relevant for welfare and monetary policy targeting.
- RBI prefers CPI because it reflects final consumer prices and service-sector inflation, which dominate modern consumption patterns and directly affect household budgets.
CPI Base Year Concept
Base Year Role
- Base year (index = 100) provides a benchmark to compare price changes over time, enabling consistent inflation measurement and long-term trend analysis for policymaking and research.
- Periodic revision ensures the reference reflects current consumption realities rather than outdated economic structures.
Need for Revision
- Rising incomes, urban lifestyles, digital payments, and service-sector expansion alter spending patterns, making older baskets unrepresentative and distorting inflation signals used for policy calibration.
- Without revision, CPI risks over- or underestimating real inflation, leading to inappropriate interest-rate and welfare decisions.
Features of CPI 2024 Series
Updated Weights
- Weights derived from HCES 2023–24 assign higher importance to services, telecom, and transport, and lower weight to declining-share items, improving representativeness of actual household spending.
- Reflects diversification of consumption beyond food toward services and lifestyle expenditures.
Expanded Basket
- Basket updated to include emerging services and digital consumption categories, capturing modern lifestyle changes, rising discretionary spending, and platform-based purchases across urban and semi-urban households. Ensures inflation reflects evolving consumption realities.
Online Price Inclusion
- Incorporates online prices for airfares, telecom, and digital services, complementing physical surveys and aligning CPI with e-commerce-driven consumption patterns and dynamic pricing realities. Improves coverage of modern markets.
Methodological Upgrades
Computer-Assisted Collection
- CAPI-based price collection reduces manual errors, enables real-time validation, and improves timeliness, strengthening reliability of high-frequency inflation data used in policy decisions. Enhances data accuracy.
Administrative Data Use
- Greater reliance on official sources for rail fares, fuel, postal charges, and PDS prices reduces survey bias and increases precision in regulated-price items. Improves consistency and credibility.
Data Integration
- Integration of survey data, administrative records, and digital prices creates a wider database, enabling cross-verification and improving robustness of inflation estimates. Supports evidence-based policymaking.
Policy Significance
Monetary Policy Anchor
- RBI’s flexible inflation targeting framework uses CPI to guide repo-rate decisions, aiming to balance growth and price stability while anchoring inflation expectations. Accurate CPI improves policy transmission.
Welfare & Indexation
- CPI guides DA revisions, pensions, wage contracts, and social benefits, protecting real incomes of salaried and vulnerable groups against inflation erosion. Critical for welfare calibration.
Global Comparability
- Alignment with international standards improves cross-country inflation comparisons while retaining India-specific features, aiding investors and multilateral assessments. Enhances credibility globally.
Challenges
Informal Market Capture
- Large informal markets and regional diversity complicate uniform price capture, risking localized mismeasurement and representational gaps in the index. Requires adaptive sampling.
Rapid Consumption Shifts
- Fast-evolving digital economy and changing preferences may outpace revision cycles, necessitating more frequent updates to maintain relevance. Calls for agile statistics.
Cost–Quality Trade-off
- High-frequency, tech-driven data improves quality but requires greater resources, training, and infrastructure investments in statistical systems. Balancing cost and precision remains key.
Way Forward
Frequent Updates
- Shorter revision cycles reduce structural bias, ensuring CPI reflects evolving consumption and improves policy responsiveness. Keeps index contemporary.
Big Data Integration
- Leveraging GST data, scanner data, and digital transactions can provide granular, real-time price signals. Enhances timeliness and coverage.
Statistical Literacy
- Public understanding of inflation metrics reduces misinterpretation and builds trust in official statistics. Supports informed discourse.
Can we police AI fakes in the age of whizzy tech?
Source : Live Mint
Why in News?
Amended IT Rules, 2026 on AI Content
- Amended IT Rules 2026 mandate takedowns of non-consensual intimate imagery within 2 hours, other unlawful content within 3 hours, compulsory AI-content labelling, and safeguards against CSAM, explosives, and fraudulent deepfakes.
- Shift from earlier calibrated restraint to stricter compliance, signalling India’s move toward harder AI regulation amid rising deepfake harms, impersonation frauds, and synthetic content misuse.
Relevance
GS II — Polity & Governance
- Fundamental Rights & Regulation – Article 19(1)(a) vs 19(2): free speech vs reasonable restrictions; proportionality in regulating deepfakes, misinformation, AI harms.
- Digital Governance : Tests state regulation of Big Tech, platform liability, and IT Act rule-making, reflecting governance in the digital public sphere.
GS III — Science & Tech + Internal Security
- Emerging Technology Governance : AI regulation as frontier S&T governance balancing innovation, ethics, and safety-by-design.
- Cybersecurity & Information Integrity : Deepfakes threaten elections, national security, and finance, making AI misuse a hybrid security risk.
Practice Question
- “Regulating AI-generated content requires balancing free speech with harm prevention.”
Discuss in the context of India’s amended IT Rules, 2026.(250 Words)
Basics
What is Generative AI?
- Generative AI creates text, images, audio, or video autonomously using large datasets and models, enabling realistic impersonation and synthetic media that blur lines between reality and fabrication.Expands innovation but raises risks.
Deepfakes — Meaning
- Deepfakes are AI-generated or manipulated media that convincingly mimic real persons’ faces or voices, enabling misinformation, reputational harm, political manipulation, and financial fraud.Major governance concern.
Existing Legal Framework
- IT Act 2000, Digital Personal Data Protection Act 2023, and IT Rules provide platform liability and data safeguards, but no dedicated AI law exists yet.Regulation remains evolving.
Key Provisions
Takedown Timelines
- Platforms must remove NCII/deepfakes within 2 hours of complaint and other unlawful content within 3 hours of valid orders, creating one of the world’s strictest response timelines.Prioritises harm prevention.
Mandatory Labelling
- AI-generated content must be clearly labelled, aiming to improve transparency and reduce deception in public discourse and political communication.Supports informed consumption.
Prohibited Content Controls
- Platforms must prevent creation or spread of CSAM, explosives-related content, and fraudulent deepfakes, embedding safety-by-design obligations into AI systems.Focuses on high-risk harms.
Grievance Redressal
- User complaints must be resolved within 7 days, strengthening accountability and time-bound remedies.Enhances user protection.
Global Comparisons
International Benchmarks
- Germany’s NetzDG mandates 24-hour removal of manifestly illegal content; EU DSA requires expeditious compliance; Australia eSafety allows 24-hour takedowns.India’s deadlines are stricter.
Regulatory Trend
- Democracies are converging on platform accountability and rapid takedowns to address online harms without fully stifling innovation.Balancing act continues.
Implementation Challenges
False Positives Risk
- Tight deadlines may push platforms to remove first, verify later, raising wrongful removals and delayed restoration appeals.Risks chilling speech.
Contextual Judgement
- India’s linguistic diversity and cultural nuance complicate automated detection, especially distinguishing satire, art, or political commentary from harmful deepfakes.AI moderation limits exist.
Traceability Limits
- Metadata stripping, watermark degradation, and open-source models reduce traceability; provenance tools may be bypassed by sophisticated actors.Enforcement complexity rises.
Surveillance Concerns
- Traceability mechanisms could expose whistleblowers or lawful speakers, creating privacy and civil-liberty risks if misused.Needs safeguards.
Constitutional & Governance Angle
Free Speech Balance
- Article 19(1)(a) protects speech; restrictions under 19(2) must be reasonable, targeting clearly unlawful content like CSAM, fraud, or incitement.Proportionality essential.
Due Process
- Clear definitions, transparency in takedowns, and independent oversight ensure legitimacy and prevent arbitrary censorship.Builds trust.
Way Forward
Clarity & Definitions
- Precise legal definitions for deepfakes, NCII, and harmful AI content reduce ambiguity and over-compliance.Improves predictability.
Transparency & Appeals
- Publish takedown statistics, reasons, and swift appeal mechanisms to correct false positives.Strengthens accountability.
Tech + Legal Mix
- Combine cryptographic provenance, watermarking, platform monitoring, and deterrent penalties to raise cost of deception.Layered defence works better.
Independent Oversight
- Empower neutral regulators or appellate bodies to review platform actions, ensuring balanced enforcement.Protects rights.
